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A Digital Risk Twin For The Design And Certification Of A Distributed Space Based Space Surveillance System, Samuel Hilton

Small Satellite Conference

Objectives

• Development of a Digital Risk Twin (DRT) of a Distributed Satellite System Mission to perform Preliminary Mission Reliability Estimates
• Quantify mission reliability considering platform reliability and required System of System s (SoS) configuration for mission assurance
• Provide ability to perform rapid trade studies on Mission Reliability given varied SmallSat platform and distributed configuration requirements

Towards Comprehensive Ai-Based Onboard Fdir: System Design And First Results, Luca Manca, Gianluca Campagna, Riccardo Maderna, Gabriele Giordana

Small Satellite Conference

Health monitoring of spacecrafts is a crucial task in Space operations. Fault Detection, Isolation and Recovery (FDIR) plays a critical role in ensuring the safety and successful operation of a spacecraft by detecting and isolating faults, and then executing recovery actions. Currently, the FDIR process is carried out mostly on ground, with only anomaly detection typically performed onboard the spacecraft using out-of-limit (OOL) threshold techniques, whereas fault isolation and recovery is managed by operators on the ground.

This approach has two major limitations. Firstly, OOL approach is not capable of identifying subtle anomalies that occur within the parameters’ nominal operational …

Toward Autonomous Guidance And Control: A Robust Ai-Based Solution For Low-Thrust Orbit Transfers, Matteo Stoisa, Luca Romanelli, Federica Paganelli Azza, Pietro De Marchi, Mattia Varile

Small Satellite Conference

The focus of our initial application scenario centers around a low-thrust orbit transfer in Low-Earth Orbit (LEO). This specific use-case has been chosen due to its inherent challenges, including the requirements for robustness and real-time computation.

We propose an AI-based solution capable of autonomous and robust on-board G&C. The core of our approach leverages a Deep Neural Network (DNN) trained through Reinforcement Learning (RL) techniques. Our method aims at enhancing a traditional guidance approach by managing environmental perturbations, it processes the on-board navigation coordinates and provides the thrust to be imposed by the propulsion subsystem.

Our approach demonstrates effectiveness in …

Development Of Monopropellant 98% Htp Thrusters For Small Satellite Propulsion Modules: Technical Challenges And Solutions, Pawel Surmacz, Adrian Parzybut, Zbigniew Gut, Mariusz Rosiak, Michal Alaszkiewicz

Small Satellite Conference

No abstract provided.

Signal-Agnostic Technique For Satellite Doppler Correction, Salwan Damman, Nazia Mozaffar, Brendan Hill

Small Satellite Conference

Low Earth Orbit satellites impart a Doppler shift on transmitted signals. This Doppler shift imposes challenges on the receiver design. Optimum band-edge filters can measure the Doppler offset, and frequency-locked loops (FLLs) containing them can correct the Doppler offset. However, optimum band-edge filters require knowledge of the structure of the signal of interest in order to compute the filter coefficients. Prefilter delay-multiply elements can be used to generate a Doppler tone that can be placed in an FLL, but this technique also requires knowledge of the signal structure and is not well suited for frequency shift keyed signals. It is …

Breaking The Smallsat Barriers To Sub-50cm Imaging, Hamilton Law, Alex Da Silva Curiel, Andrew Haslehurst, Steven Knox, Victoria Irwin, Martin Sweeting

Small Satellite Conference

New cutting-edge imaging sensors can now reduce instrument size and mass, leading to mission cost savings, and bring sub-50cm imaging capability into the realm of small satellites. Whilst aperture is essential to achieving resolution, half-pixel shifted sensor architectures decouple achievable Ground Sampling Distance (GSD) from the native ground projected pixel. This facilitates the deployment of Very High Resolution (VHR) small satellite constellations featuring improved Signal-to-Noise performance and increased area collection rates compared to push-frame systems.

A fundamental limitation to the theoretical performance of an optical system is imposed by its aperture diameter; hence, for a given aperture, the aim is …

Confronting Or Linking Csp And Ccsds? A View On How To Operate Small Satellites Today, Pierre-Alexis Lagadrillière, Tobias Brügge, Kay Müller

Small Satellite Conference

CubeL was launched early 2021 and is the first COTS cubesat which the German Space Operations Center (GSOC) of DLR is operating. It carries 3 of the most typical space-to-ground communication systems with its UHF transceiver, its S-band transceiver and its laser terminal. Main aim is to demonstrate the capabilities of the miniaturized laser terminal for high speed communications up to 100Mbps. The second aim of this cubesat is to test operations between the on-board S-band transceiver with its native CSP and GSOC’s multi-mission environment based on CCSDS and ECSS protocols and standards, e.g. the CCSDS space packet protocols.

In …

Moon Orbiter "Izumi" For Lunar Water Exploration, Kentaro Taniguchi, Miwa Tsurumi, Ryusei Komatsu

Small Satellite Conference

NASA's Artemis program focuses on the water resources on the Moon. As lunar exploration probes with high spatial resolutions can identify potential drilling points on the lunar surface, this study proposes a mission that focuses on neutrons generated by galatic cosmic rays that leak into space and contain information regarding the amount of water within the lunar subsurface. Neutron detectors used in previous lunar exploration mission probes have encountered challenges in achieving both high spatial resolution and statistical reliability. To overcome these challenges, the proposed mission satellite is equipped with the world's first imager proposed for thermal neutrons. The satellite …

Lost: An Open-Source Suite Of Star Tracking Software, Mark Polyakov, Edward Zhang, Karen Haining

Small Satellite Conference

We present LOST: Open-source Star Tracker (LOST), a suite of star tracking software particularly suitable for small satellite missions with limited computing resources and low-cost cameras. LOST contains implementations of a number of previously-proposed star tracking algorithms and a flexible framework for running and evaluating these algorithms. Our evaluation finds that LOST's algorithms are simultaneously able to maintain a strong combination of accuracy, runtime, and memory usage. In scenarios representative of a low-cost star tracker, LOST correctly identifies over 95% of images, and importantly, performs the entire star tracking pipeline in less than 35 milliseconds on a Raspberry Pi while …

Responding To Disproportionate Skin Cancer Rates Affecting Adult Men Aged 18-60, Aaron Thompson

Capstone Collection

Skin cancer is a deadly disease that kills significantly more men than women every year. At the same time, women are more than twice as likely to apply daily sun protection factor (SPF) than men. This research study explores how key stakeholders within the skin care industry have responded to the data showing increasing disparities between male and female skin cancer rates. To fulfill the objectives of this research study, qualitative data was collected from six semi-structured interviews with adult males between the ages of 18 and 60. The interviews were intentionally designed to engage with the American, adult male’s …

Static Malware Family Clustering Via Structural And Functional Characteristics, David George, Andre Mauldin, Josh Mitchell, Sufiyan Mohammed, Robert Slater

SMU Data Science Review

Static and dynamic analyses are the two primary approaches to analyzing malicious applications. The primary distinction between the two is that the application is analyzed without execution in static analysis, whereas the dynamic approach executes the malware and records the behavior exhibited during execution. Although each approach has advantages and disadvantages, dynamic analysis has been more widely accepted and utilized by the research community whereas static analysis has not seen the same attention. This study aims to apply advancements in static analysis techniques to demonstrate the identification of fine-grained functionality, and show, through clustering, how malicious applications may be grouped …

Using Geographic Information To Explore Player-Specific Movement And Its Effects On Play Success In The Nfl, Hayley Horn, Eric Laigaie, Alexander Lopez, Shravan Reddy

SMU Data Science Review

American Football is a billion-dollar industry in the United States. The analytical aspect of the sport is an ever-growing domain, with open-source competitions like the NFL Big Data Bowl accelerating this growth. With the amount of player movement during each play, tracking data can prove valuable in many areas of football analytics. While concussion detection, catch recognition, and completion percentage prediction are all existing use cases for this data, player-specific movement attributes, such as speed and agility, may be helpful in predicting play success. This research calculates player-specific speed and agility attributes from tracking data and supplements them with descriptive …

Traditional Vs Machine Learning Approaches: A Comparison Of Time Series Modeling Methods, Miguel E. Bonilla Jr., Jason Mcdonald, Tamas Toth, Bivin Sadler

SMU Data Science Review

In recent years, various new Machine Learning and Deep Learning algorithms have been introduced, claiming to offer better performance than traditional statistical approaches when forecasting time series. Studies seeking evidence to support the usage of ML/DL over statistical approaches have been limited to comparing the forecasting performance of univariate, linear time series data. This research compares the performance of traditional statistical-based and ML/DL methods for forecasting multivariate and nonlinear time series.

A Hybrid Ensemble Of Learning Models, Bivin Sadler, Dhruba Dey, Duy Nguyen, Tavin Weeda

SMU Data Science Review

Statistical models in time series forecasting have long been challenged to be superseded by the advent of deep learning models. This research proposes a new hybrid ensemble of forecasting models that combines the strengths of several strong candidates from these two model types. The proposed ensemble aims to improve the accuracy of forecasts and reduce computational complexity by leveraging the strengths of each candidate model.

Development Of Tactical And Strategic Operations Software For Nasa's Lunar Flashlight Mission, Mason Starr

Small Satellite Conference

Lunar Flashlight (LF) is an interplanetary CubeSat mission designed to demonstrate the use of a novel green monopropellant propulsion system and characterize lunar surface ice with a near-infrared laser array and reflectometer. LF is also the first Jet Propulsion Laboratory (JPL) mission to be operated entirely by students. While JPL provided baseline tools to Georgia Tech (GT), bespoke tools and software were developed by GT operators. Four tools developed by the author are discussed in this paper: (1) Downlink Helper is a Graphical User Interface (GUI) tool which improves the tactical downlink of recorded spacecraft telemetry. The tool automatically creates …

Cost-Effective Payload Operations Planning Software For Complex Small Spacecraft Mission Operations, Willard Farmer

Small Satellite Conference

As small spacecraft become more capable, so does the complexity of their operations. Searching for potential concurrent observation or access opportunities and ensuring they are compatible with one another may become tedious and repetitive for operators to manually compute. Currently available commercial-off-the-shelf tools that automate this process are capable but expensive. To address this problem, a new payload operations planning tool has been developed by the Space Flight Laboratory to handle the deterministic aspects of mission planning, such as: detecting observation opportunities, validating observations in a schedule, and generating lists of commands to be sent to satellites. This lightweight tool …

Evaluating Rotation-Equivariant Deep Learning Models For On-Orbit Cloud Segmentation, Alex Meredith

Small Satellite Conference

Cloud detection in satellite imagery is key for autonomously taking and downlinking cloud-free images of a target region as well as studying cloud-climate interactions and calibrating microwave radiometers. We propose a C₈-equivariant dense U-Net, a rotation-equivariant deep learning model, trained on visible-spectrum, long-wave infrared (LWIR), and short-wave infrared (SWIR) imagery for on-orbit cloud detection. We train this model on the SPARCS¹ dataset of Landsat 8 images and compare it to three related deep learning models, two rule-based algorithms, and to the literature. Additionally, we compare a C₈-equivariant dense U-Net trained on VIS, LWIR, and SWIR …

T Cell Receptor Engineering Targeting Foxm1 For The Treatment Of Lung Cancer, Isabel M. Perez-Sandi, Alexandre Reuben, Minying Zhang, Hui Nie, Peixin Jiang, Cassian Yee, Gregory Lizee, John V. Heymach

Summer Experience 2023

No abstract provided.

Data On Deck: A Case Study Of A Historic Undersea Film And Video Digitization Project, Karen Urbec Mlis, Ca, Audrey Mickle Mlis, Lisa Raymond

Journal of Contemporary Archival Studies

In 2021, the Woods Hole Oceanographic Institution (WHOI) Data Library and Archives (DLA), a part of the MBLWHOI (Marine Biological Laboratory Woods Hole Oceanographic Institution) Library, received a grant from the Council on Library and Information Resources (CLIR) Recordings at Risk (RAR) program to catalog, digitize, preserve, and make available historic films and videos of Alvin, the first-of-its-kind manned submersible vessel that has shown us more of the deep ocean than had ever been possible and transformed our understanding of life on Earth.

These moving images have not been accessible to researchers and were far past the intended life cycle …

Functional Connectivity Varies Across Scales In A Fragmented Landscape, Kate I. T. Bird, Daniel R. Uden, Craig R. Allen

School of Natural Resources: Faculty Publications

Species of different sizes interact with the landscape differently because ecological structure varies with scale, as do species movement capabilities and habitat requirements. As such, landscape connectivity is dependent upon the scale at which an animal interacts with its environment. Analyses of landscape connectivity must incorporate ecologically relevant scales to address scale-specific differences. Many evaluations of landscape connectivity utilize incrementally increasing buffer distances or other arbitrary spatial delineations as scales of analysis. Instead, we used a mammalian body mass discontinuity analysis to objectively identify scales in the Central Platte River Valley (CPRV) of Nebraska, U.S.A. We implemented a graph-theoretic network …

Convergence: Eos News And Updates, August 2023, Unh Institute For The Study Of Earth, Oceans And Space

Convergence: EOS News and Updates

No abstract provided.

An Allelic Series Of Spontaneous Rorb Mutant Mice Exhibit A Gait Phenotype, Changes In Retina Morphology And Behavior, And Gene Expression Signatures Associated With The Unfolded Protein Response., George Murray, Jason A. Bubier, Oraya Zinder, Belinda S. Harris, James Clark, Mia-Cara Christopher, Courtany Hanley, Harianto Tjong, Meihong Li, Chew Yee Ngan, Laura G Reinholdt, Robert W. Burgess, Abigail L D Tadenev

Faculty Research 2023

The Retinoid-related orphan receptor beta (RORβ) gene encodes a developmental transcription factor and has 2 predominant isoforms created through alternative first exon usage; one specific to the retina and another present more broadly in the central nervous system, particularly regions involved in sensory processing. RORβ belongs to the nuclear receptor family and plays important roles in cell fate specification in the retina and cortical layer formation. In mice, loss of RORβ causes disorganized retina layers, postnatal degeneration, and production of immature cone photoreceptors. Hyperflexion or "high-stepping" of rear limbs caused by reduced presynaptic inhibition by Rorb-expressing inhibitory interneurons of the …

August 9, 2023 Greenmail, University Of Alabama At Birmingham

GreenMail (student newsletter through 2024)

No abstract provided.

Ud Student Gains Technical Skills, Personal Growth From Research Experience, University Of Dayton

Blog: The Dayton Engineer

Strong and flexible — those are the words UD student Julian Pabon uses to describe the materials needed for a morphing wing, the subject of his research in UD’s wind tunnel.

Reducing Hospital-Acquired Clostridium Difficile, Tracy Esposo

Master's Projects and Capstones

Background: This project focused on implementation of clostridium difficile (C. diff) education sessions at Hospital A, a not-for-profit, short-term, acute care hospital serving the Greater Sacramento community. It comprises of 241 staffed beds in the medical-surgical, telemetry, and intensive care units.

Problem: My Clinical Nurse Leader project focused on preventing hospital-acquired C. diff. At Hospital A, there were 19 hospital-acquired C. diff cases for the 2022 performance year. Of the 19 clostridium difficile cases, 12 were related to C. diff testing criteria fall-outs.

Despite huddling with staff on opportunities and providing education through health stream modules, Hospital A continues to …

End To End Routing Algorithms In Arbitrary Networks, Nada Alzaben

Computer Science and Engineering Theses and Dissertations

The End to End Routing Problem in computer communication networks is the problem of scheduling fixed routes through the network over time. All the packets in a single communication flow follow an assigned route and all flows are routed such that some function of the flows is optimized. A flow is a sequence of packets that are released by some source node and sent over the communication network to a destination node. Multiple objective functions may be used to evaluate the performance of the network. Common objective functions include minimize the mean wait time, minimize the total wait time, minimize …

Butte Priority Soils Operable Unit (Bpsou) Final Insufficiently Reclaimed Sites – Field Sampling Plan (Fsp) Bres No. 84 – Mandan Park Play Area, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Unlocking Insights Into Crop Growth And Nutrient Distribution: A Geospatial Analysis Approach Using Satellite Imagery And Soil Data, Olatunde D. Akanbi, Brian Gonzalez Hernandez, Erika I. Barcelos, Arafath Nihar, Laura S. Bruckman, Yinghui Wu, Jeffrey Yarus, Roger H. French

Student Scholarship

Accurate monitoring of crop growth and nutrient distribution is crucial for optimizing agricultural practices, promoting a sustainable environment, and ensuring long-term food production. In this study, we propose a novel and comprehensive approach to monitor crop growth and nutrient distribution in large-scale agricultural landscapes. Our methodology combines advanced geospatial and temporal analysis techniques, providing valuable insights into the intricate relationships between crop health, soil nutrients, and other essential soil properties.

To monitor vegetation dynamics, we obtained data from the IBM EIS (Environment Intelligence Suite) and processed it using our HPC (High-Performance Computing) infrastructure. This is ingested into our CRADLE (Common …

Svb And Beyond: The Banking Stress Of 2023, Viral V. Acharya, Matthew P. Richardson, Kermit L. Schoenholtz, Bruce Tuckman

Documents

No abstract provided.

Influence Of Ultrasound Machine Settings On Quantitative Measures Derived From Spatial Frequency Analysis Of Muscle Tissue, Scott K. Crawford, Stephanie A. Kliethermes, Bryan C. Heiderscheit, Greg Bashford

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Background Ultrasound is a powerful tool for diagnostic purposes and provides insight into both normal and pathologic tissue structure. Spatial frequency analysis (SFA) methods characterize musculoskeletal tissue organization from ultrasound images. Both sonographers in clinical imaging and researchers may alter a minimized range of ultrasound settings to optimize image quality, and it is important to know how these small adjustments of these settings affect SFA parameters. The purpose of this study was to investigate the effects of making small adjustments in a typical default ultrasound machine setting on extracted spatial frequency parameters (peak spatial frequency radius (PSFR), Mmax, Mmax%, and …